Global States and Regions Annual Disclosure Update 2019€¦ · states and regions in this...

Global States and Regions Annual Disclosure Update 2019 Annex | November 2019

Projected Impact of Disclosed Targets

Aim

The aim of the analysis is to project the potential impact of disclosed emissions reduction targets from states

and regions using projected emissions trajectories to 2050. The analysis compares the ambition of disclosed

targets from 49 states and regions to the ambition of the Nationally Determined Contributions (NDCs) and

long-term targets of their national government counterparts. Additionally, the analysis compares the states

and regions and national government trajectories to a 1.5°C trajectory to assess whether the targets are

aligned with the 1.5°C goal.

State and Regional GHG Emissions Projections

Scenario

Total GHG Emissions (GtCO2)

2010 2017 2020 2030 2040 2050

NDCs Pathway 2.84 2.49 2.15 Longer-Term Pathway 2.11 1.51 0.92

States and Regions 2.84 2.50 1.74 1.03 0.72

1.5°C 2.84 2.66 1.05 0.50 0.17

Historical Emissions 3.06 2.84

Data Sources

• State and regional population and emissions data was primarily self-reported as part of the

Annual Disclosure process through CDP’s States and Regions 2019 questionnaire and was

supplemented with data from official government websites.

• NDCs and Long-Term Pathway data was taken from the Climate Action Tracker (CAT)

• Data for 1.5°C Low Energy Demand trajectory was taken from IAMC 1.5°C Scenario Explorer

hosted by IIASA

• National population projections were taken from The World Bank

1.5°C Low Energy Demand Scenario

The 1.5°C Low Energy Demand scenario is taken from a report by Grubler et al., 2018, which assesses

a world of limiting global warming to 1.5°C through a rapid phase out of fossil fuels and thus reducing

energy demand to around 40% lower than today. This scenario excludes any negative emission

technologies, relying on natural solutions to absorb carbon from the atmosphere. It was chosen as the

scenario which could feasibly be achieved by states and regions; to account for their advancements in

renewable energy, as well as the barriers preventing them from implementing negative emission

technologies such as bio-energy with carbon capture and storage.

https://climateactiontracker.org/

https://data.ene.iiasa.ac.at/iamc-1.5c-explorer/#/login?redirect=%2Fworkspaces


https://datacatalog.worldbank.org/dataset/population-estimates-and-projections

Data Requirements to be Included in the Analysis

States and regions:

1. At least one region-wide GHG emissions reduction target

2. Region-wide GHG emissions data at both base year and year of latest GHG inventory

3. Historical population records between 2010 and 2017

4. Projected population figures from 2017 up to 2050

National Governments:

1. GHG emissions from 2010 to year of latest GHG inventory

2. CAT NDC pathways to 2030

3. CAT long-term pathway to 2050

4. National population projections from 2010 to 2050

Step 1 – Population:

The first step of the analysis was to project the population for each state and region from 2010 up to

2050. By gathering and inputting population figures obtained from CDP’s States and Regions 2019

questionnaire and government statistical websites, the gaps between two data points were filled using

a Compound Annual Growth Rate (CAGR). Previous CAGR from the last interval has been used to

project data in cases where population projections up to 2050 were not available.

Step 2 – Emissions:

The second step was to project emissions from 2010 to 2050. Here, we used disclosed emissions

reduction targets to calculate what the emissions would be for each state or region in the specified

target years assuming they met their targets. Following a similar process to step 1, the previous CAGR

was used to fill in missing values and to project values up to 2050 if no long-term target was reported.

Step 3 – Business-As-Usual (BAU) emissions:

Using the resulting population and emissions data from steps 1 and 2, a BAU emissions projection was

calculated for each state and region from 2017 to 2050. Here a GHG intensity value (GHG per capita)

was calculated at 2017 for each state and region. This was then multiplied by the projected population

value of each year from 2017 to 2050 to achieve a BAU projection. Totalling the BAU emissions

projections for each state gave the total BAU projection. The purpose of the BAU projection is to use

it in step 5 of the analysis to adjust national government targets to the state and regional BAU

projection.

This is a simple projection assuming that as population increases, the emissions of that state or region

will also increase proportionally. The BAU projection assumes that the GHG intensity of the disclosing

governments would stay the same between 2017 and 2050 with no significant climate mitigation

action taken.

Step 4 – Country Data:

From Climate Action Tracker, we downloaded scenario data for each country represented by the

states and regions in this analysis: Australia, Brazil, Canada, the European Union, Mexico, Norway, and

the USA. This data set provided us with the estimated emissions trajectories for the respective

governments in each scenario. The data we used for the analysis were the historical emissions dating

https://climateactiontracker.org/

back to 2010, and future emissions projections from both NDCs Pathway to 2030 and the Long-Term

Pathway, beyond the NDCs, to 2050.

Step 5 – Vectors:

The total GHG emissions from the 7 countries is much larger and not accurately comparable to the

total emissions from the 49 states and regions used in this analysis. For this reason, we projected a

hypothetical emissions trajectory that assumes states and regions will implement only NDCs and Long-

Term pathways laid out by their respective national governments. To do this, we calculated the

emissions per capita of each country from 2017 to 2050 and used this to calculate vectors. We applied

the vectors to the state and regional BAU emissions projection and adjusted it to reflect

implementation of national targets. This approach allowed us to better compare the targets between

the two groups.

Following the same principles used for NDCs and Long-Term pathways, we also calculated vectors to

adjust the 1.5°C scenario because this was originally based on a global emissions trajectory.

Assumptions and Limitations

Achieving targets:

Both the projections of national and state and regional governments assume that all governments will

fully achieve their targets.

Long-term pathways:

For national, state, or regional governments without a long-term target beyond 2030, we have taken

previous targets and assumed they will carry on with the same rate of decarbonisation to 2050 as set

out in their mid-term targets.

BAU trajectory:

The BAU trajectory does not account for any economic, political, or large-scale climatic activity

occurring within the region. Thus, we assume population growth based on the projections reported

by governments. It is a simple projection assuming that emissions will increase proportionally to

increases in population based on the emissions profile in 2017.

Land use, land use change and forestry (LULUCF):

CAT scenario data excludes all LULUCF emissions from national projections including carbon sinks. Due

to limitations in measurement and reporting, the disclosed data varies across each state or region,

with some governments including LULUCF emissions, others excluding just sinks, and others reporting

net emissions.

Gross vs net emissions inconsistencies:

To overcome some of the inconsistencies in gross or net emissions being reported, we have tried to

ensure that when projecting emissions of each state or region that we remain consistent by using

gross emissions at base year to gross emissions in target year, or net to net. This helps to project an

accurate trajectory and avoid under or over estimating the emissions trajectory.

Greenhouse gas reporting inconsistencies:

We have compared the projections to a 1.5°C CO2 trajectory which projects carbon emissions reaching

zero around mid-century. Due to the increased potency and higher global warming potential of other

gases such as methane and hydrofluorocarbons, the IPCC projects that all GHG emissions will need to

reach net-zero around 2070 to limit global warming to 1.5°C by 2100. Due to different reporting

methodologies, we have seen differing results in what gases have been reported by state and regional

governments. Some governments have reported all GHGs in their inventories and have set emission

reduction targets focusing on all gases, whilst others didn’t disclose which gases they have measured,

and others focused solely on CO2.

States and Regions in the Projection Analysis

State / Region name Country

Aland EU

Andalusia EU

Attica EU

Australian Capital Territory Australia

Azores EU

Baden-Württemberg EU

Basque Country EU

Bavaria EU

British Columbia Canada

Brittany EU

California USA

Cantabria EU

Catalonia EU

Comunidade Intermunicipal do Médio Tejo EU

Connecticut USA

Drenthe EU

Emilia-Romagna EU

Galicia EU

Hawaii USA

Helsinki-Uusimaa EU

Hesse EU

Jämtland EU

La Reunion EU

Lombardy EU

Lower Austria EU

Minnesota USA

Navarra EU

New South Wales Australia

New York State USA

Newfoundland and Labrador Canada

Nordland Norway

North Brabant EU

North Rhine-Westphalia EU

Northwest Territories Canada

Oregon USA

Québec Canada

Queensland Australia

Rhineland-Palatinate EU

Rio de Janeiro State Brazil

São Paulo State Brazil

Schleswig-Holstein EU

Scotland EU

South Australia Australia

Victoria Australia

Thuringia EU

Wales EU

Wallonia EU

Washington USA

Yucatán Mexico

Table 1: region-wide GHG base year emissions reduction targets

Government Base year 2020 2025 2030 2035 2040 2045 2050

Aland 2005 60%

Andalusia 2005 26%

Attica 2008 20%

Australian Capital Territory

1990 40% 50% 65-75% 90-95% 100%

Baden-Württemberg1

1990 25% 42% 90%

Basque Country 2005 30% 80%

British Columbia 2007 40% 60% 80%

Brittany 2012 51%

California2 1990 25% 40% 65% 80%

Catalonia 2005 &

1990 25%3 40% 65% 100%

Comunidade Intermunicipal do Médio Tejo

2008 23%

Connecticut 1990 &

2001 10%4 45% 80%

Drenthe 1990 20%

Helsinki-Uusimaa 1990 80%

Hesse 1990 30% 40% 55% 90%

Huánuco 1990 80%

Jämtland 1990 50%

La Réunion 2011 10%

Lombardy 2005 20% 40% 80%

Lower Austria 2005 36%

Madeira 1990 30% 80%

Minnesota 2005 80%

Navarra 2005 20% 45%

New York State 1990 40% 85%

Newfoundland and Labrador

1990 & 2005

10% 30%5 75%

North Brabant 1990 50%

North Rhine-Westphalia

1990 80%

Northwest Territories

2005 30%

Oregon 1990 10% 75%

Québec 1990 20% 37.5% 80%

Queensland 2005 20%

Rhineland-Palatinate

1990 40%

1 GHG reduction targets of Baden-Württemberg have been added post annual disclosure period 2 Target as described per Executive Order B-55-18 3 Catalonia's 2020 target has a base year of 2005 4 Connecticut's 2020 target has a base year of 1990 5 Newfoundland and Labrador's 2030 target has a base year of 2005

São Paulo State 2005 20%

Sardinia 1990 83%

Schleswig-Holstein

1990 40%

Scotland6 1990 56% 75% 90% 100%

South Australia 1990 60%

Southern Ostrobothnia

2010 20%

Thuringia 1990 70% 80% 95%

Ucayali 1990 80%

Victoria 2005 15% 100%

Wales 1990 40% 80%

Wallonia 1990 95%

Washington 1990 25% 50%

West Kalimantan 2000 29%

Yucatán 2005 40%

Table 2: region-wide GHG intensity emissions reduction targets

Government Intensity Target

Gujarat Reduce the emissions intensity of GDP by 33%–35% by 2030 below 2005 levels

Rio de Janeiro State Reduce intensity of region-wide emissions to 0.13 tonnes CO2e/R$ 1,000 by 2030

Upper Austria Reduce energy-related GHG emissions intensity by 33% by 2030

Upper Austria Reduce energy-related GHG emissions intensity by 70-90% by 2050

Table 3: region-wide baseline scenario emissions reduction targets

Government Baseline Scenario Target

Azores Reduce region-wide emissions by 38% in 2030 compared to a business-as-usual (BAU) scenario

Chungcheongnam-Do

Reduce region-wide emissions by 28.9% in 2020 compared to a business-as-usual (BAU) scenario

Nordland Reduce region-wide emissions by 30% in 2020 compared to a business-as-usual (BAU) scenario

Table 4: region-wide fixed level emissions reduction targets

Government Fixed Level Target

Bavaria7 Bavaria aims to reduce emissions to under 5 tonnes of CO2e per capita by 2030

Bavaria aims to reduce emissions to under 2 tonnes of CO2e per capita by 2050

California California aims to reduce emissions to 1990 levels by 2020

California2 California’s statewide goal is to achieve carbon neutrality as soon as possible, and no later than 2045

6 Scotland’s updated targets have been agreed by Parliament on 25 September 2019 but are not yet in force. The current statutory targets (42% by 2020, 80% by 2050) are in place for the transition year. 7 GHG reduction targets of Bavaria have been added post annual disclosure period

Hawaii Hawaii aims to reduce emissions to 1990 levels by 2020

Hawaii Hawaii aims to achieve net zero emissions by 2045

Nord Trøndelag Nord Trøndelag aims to achieve net zero emissions by 2050

Queensland Queensland aims to achieve net zero emissions by 2050

Washington Washington aims to reduce emissions to 1990 levels by 2020

Table 5: GHG reduction targets and progress towards them in states and regions with net-

zero targets

State Percentage reduction target

Target year

% progress towards target

Australian Capital Territory 40 2020 -13%





California8 40 2030 4%

California8 Net-Zero 2045 N/A

Catalonia 25 2020 91%

Catalonia 40 2030 -21%



Hawaii 1990 levels 2020 107%

Hawaii Net-Zero 2045 N/A

Helsinki-Uusimaa9 80 2035 22%

New York10 40 2030 32%

New York10 85 2050 15%

Nord-Trøndelag Net-Zero 2050 N/A

Queensland 30 2030 70%

Queensland Net-Zero 2050 N/A

Scotland11 56 2020 84%

Scotland11 75 2030 62%

Scotland11 90 2040 52%

Scotland11 100 2045 47%

Victoria 15 2020 72%

Victoria 100 2050 11%

Thuringia12 70 2030 89%

Thuringia12 80 2040 78%

Thuringia12 95 2050 66%

8 California's Executive Order B-55-18 aims to achieve carbon neutrality by 2045 and includes a target of 80% reductions in carbon emissions

by 2050 and the removal of carbon dioxide from the atmosphere through sequestration in forests, soil and other landscapes 9 Helsinki-Uusimaa aims to be carbon neutral by 2035 by reducing emissions by 80% and offsetting the remaining 20% 10 New York state has committed to reduce emissions by 85% and offset the remaining 15% 11 Scotland's updated targets have been agreed by Parliament on 25 September 2019, but are not yet in force 12 Thuringia aim to pursue carbon neutrality by offsetting the remaining 5% of emissions through the development of natural carbon stocks N/A indicates fixed level targets which do not specify gross emissions reductions, so progress cannot be calculated

Table 6: progress towards 2020 GHG emissions reduction targets

Government Base year

Total emissions of

base year inventory

(metric tonnes CO2e)

Current total gross emissions (excludes sinks)

Current total net emissions

(includes sinks)

Percentage reduction

target

BAU Emissions

Target year

Target Type

Predicted emissions in target year

Progress to target

Attica 2008 33,058,527 23,761,684.00 22,832,355.00 20 2020 Base year emissions

26,446,822 141%


1990 3,196,800 3,377,000.00 3,367,000.00 40 2020 Base year emissions

1,918,080

-13%

California 1990 431,000,000 424,097,419.00 - 1990 levels 2020 Fixed level

431,000,000 102%

Catalonia 2005 58,434,374 45,072,920.00 - 25 2020 Base year emissions

43,825,781 91%

Comunidade Intermunicipal do Médio Tejo

2008 1,322,979 1,056,111.00 - 23 2020 Base year emissions

1,018,694

88%

Connecticut 1990 45,531,547 41,131,888.00 - 10 2020 Base year emissions

40,978,392 97%

Drenthe 1990 3,750,000 3,605,600.00 - 20 2020 Base year emissions

3,000,000 19%

Hawaii 1990 19,080,000 21,280,000.00 17,750,000.00

1990 levels 2020 Fixed level

19,080,000 107%

Hesse 1990 51,500,000 - 40,400,000.00 30 2020 Base year emissions

36,050,000 72%

La Reunion 2011 4,700,000 4,838,348.00 4,328,512.00 10 2020 Base year emissions

4,230,000 79%

Lombardy 2005 86,500,000 69,100,000.00 66,500,000.00 20 2020 Base year emissions

69,200,000 116%

Navarra 2005 6,635,255 5,582,511.00 - 20 2020 Base year emissions

5,308,204 79%


1990 9,437,381 10,538,113.00 10,535,042.00 10 2020 Base year emissions

8,493,643 -117%

Nordland 2009 2,900,000 3,244,112.90 - 30 3,200,000.00 2020 Baseline scenario

2,240,000 -52%

Oregon 1990 56,128,149 64,561,358.00 - 10 2020 Base year emissions

50,515,334 -150%

Québec 1990 86,455,424 78,560,583.00 - 20 2020 Base year emissions

69,164,339 46%

Rhineland-Palatinate


30,462,600 94%

Schleswig-Holstein


20,392,200 63%

Scotland 1990 76,262,950 53,545,130.00 40,521,593.00 56 2020 Base year emissions

33,555,698 84%

Victoria 2005 127,800,000 123,689,076.39 113,951,991.67 15 2020 Base year emissions

108,630,000

72%

Wales 1990 55,729,784 42,141,638.60 41,746,912.34 40 2020 Base year emissions

33,437,871 63%

Washington 1990 90,498,300 97,758,400.00 58,130,200.00 1990 levels 2020 Fixed level

90,498,300 92%

Table 7: progress towards 2030 GHG emissions reduction targets


Total emissions of

base year inventory

(metric tonnes CO2e)

Current total gross

emissions (excludes

sinks)

Current total net emissions

(includes sinks)

Percentage reduction

target

BAU Emisssions

Target year

Predicted emissions in target

year

Progress to target

Aland 2005 260,000

180,000.00 - 60 2030 104,000

51%

Andalusia 2005 66,160,077

51,759,504.00 - 26 2030 48,958,457

84%


1990 3,196,800

3,377,000.00

3,367,000.00 65 2030 1,118,880

-8%

Azores13 2014 1,724,070

1,716,777.00

1,302,380.00 38

1,393,814.00

2030 864,165 1%

Basque Country 2005 25,505,208

20,046,519.00

19,646,519.00 30 2030 17,853,646

71%

British Columbia 2007 63,641,000

62,300,000.00

61,300,000.00 40 2030 38,184,600

5%

California 1990 431,000,000

424,097,419.00 - 40 2030 258,600,000

4%

Catalonia 1990 41,577,731

45,072,920.00 - 40 2030 24,946,639

-21%

Connecticut 2001 49,221,076

41,131,888.00 - 45 2030 27,071,592

37%

Hesse 1990 51,500,000 -

40,400,000.00 55 2030 23,175,000

39%

Lombardy 2005 86,500,000

69,100,000.00

66,500,000.00 40 2030 51,900,000

58%

13 Not included in graph due to baseline scenario instead of percentage reduction target

Lower Austria 2005 13,071,000

18,247,000.00

11,640,000.00 36 2030 8,365,440

30%

Navarra 2005 6,650,328

5,582,511.00 - 45 2030 3,657,680

36%

New York State 1990 236,190,000

205,610,000.00 - 40 2030 141,714,000

32%


2005 9,861,170

10,538,113.00

10,535,042.00 30 2030 6,902,819

-23%

North Brabant 1990 21,113,000

25,300,000.00 - 50 2030 10,556,500

-40%

Northwest Territories

2005 1,564,000

1,260,000.00 - 30 2030 1,094,800

65%

Québec 1990 86,455,424

78,560,583.00 - 37.5 2030 54,034,640

24%

Queensland 2005 179,831,020

161,200,770.00

142,073,240.00 30 2030 125,881,714

70%

Scotland 1990 76,262,950

53,545,130.00

40,521,593.00 75 2030 19,065,738

62%

Thuringia 1990 33,800,000

12,641,000.00 - 70 2030 10,140,000

89%

Progress towards target in Tables 5, 6 and 7 were calculated using reported base year emissions, current emissions and calculated target emissions using

the following formula:

− Progress to target: (Emissions of base year – current emissions)/ (Emissions of base year – target emissions) x 100

Table 8: count of mitigation actions by sector

Sector Number of actions currently being implemented

Energy 735

Buildings & Lighting 721

Transport 520

Waste 488

Land use 301

Governance 295

Industry 220

Agriculture 220

Finance & Economy 203

Water 92

Healthcare 26

Total 3821

Table 9: count of reported climate change impacts

Climate change impacts reported globally Count

Increased water stress or scarcity 59

More hot days 52

More intense rainfall 50

Sea level rise 47

Flooding 39

Hotter summers 36

More frequent droughts 35

Declining water quality 31

Increased frequency of large storms 31

More frequent heat waves 31

Change in seasonality of rainfall 30

Warmer water temperatures 23

More intense droughts 21

More intense heat waves 21

Inadequate or aging infrastructure 20

Greater temperature variability 20

Drought 19

Reduced average annual rainfall 19

Coastal erosion 18

Reduced average annual snowfall 18

More frequent rainfall 12

Increased wind speeds 11

Increased average annual rainfall 11

Salinization of water bodies 9

Changes in humidity 8

Higher water prices 8

Soil salinization 7

Regulatory 5

Extreme winter conditions 5

Other 32

Total 728

Table 10: estimated magnitude of climate change impacts

Estimated magnitude of climate change impacts reported globally Count %

Serious 411 62.5%

Extremely serious 164 24.9%

Less serious 82 12.5%

Other: Seriousness of impact unknown 1 0.2%

Total 658 100%

Table 11: count of adaptation actions

Adaptation actions reported globally Count

Community engagement/education 41

Conservation awareness and education 31

Crisis management including warning and evacuation systems 27

Flood mapping 27

Incorporating climate change into long-term planning documents 23

Investment in existing water supply infrastructure 20

Real time risk monitoring 20

Watershed preservation 20

Biodiversity monitoring 19

Heat mapping and thermal imaging 19

Projects and policies targeted at those most vulnerable 19

Stormwater management (natural or man-made infrastructure) 18

Diversifying water supply (including new sources) 16

Efficiency regulations or standards 16

Tree planting and/or creation of green space 16

Sea level rise modelling 14

Water use restrictions 14

Improving monitoring 12

Resilience and resistance measures for buildings 12

Flood defences – development and operation & storage 9

Municipal water efficiency retrofits 9

Restrict development in at risk areas 9

Conservation incentives 8

Water metering 8

Crisis planning and practice exercises 7

Disease prevention measures 7

Landslide risk mapping 7

Storm water capture systems 7

Water use restrictions and standards 7

Public preparedness (including practice exercises/drills) 6

Soil retention strategies 6

Hazard resistant infrastructure design and construction 5

Implementing nature-based solutions for water 5

Improve water supply distribution method 5

Promoting and incentivizing water efficiency 5

Awareness campaign/education to reduce water use 4

Use of non-potable water outside 4

Additional reservoirs and wells for water storage 3

Diversification of water supply 3

Maintenance/repair – leaking infrastructure 3

Shading in public spaces, markets 3

Water butts/rainwater capture 3

Water smart metering 3

Air quality initiatives 2

Retrofit of existing buildings 2

Water efficient equipment and appliances 2

Diversifying power/energy supply 1

Economic diversification measures 1

Green roofs/walls 1

Use of non-potable water indoors (within building) 1

Water extraction protection 1

Water use audits 1

Other 119

Total 651

Table 12: count of adaptation actions in response to top 10 globally reported impacts of climate change (N≥3)

Top 10 climate change impacts reported globally Globally reported adaptation actions

Number of actions (N≥3)

Increased water stress or scarcity

Conservation awareness and education 21

Diversifying water supply (including new sources) 12


Water use restrictions 6


Conservation incentives 4

Investment in existing water supply infrastructure 4

Water metering 3

Municipal water efficiency retrofits 3

More hot days

Tree planting and/or creation of green space 8


Biodiversity monitoring 6



Shading in public spaces 3

More intense rainfall

Flood mapping 14

Flood defences – development and operation & storage 6


Storm water capture systems 4

Restrict development in at-risk areas 3

Real time risk monitoring 3

Landslide risk mapping 3

Sea level rise

Sea level rise modelling 13

Flood mapping 4

Restrict development in at-risk areas 3


Incorporating climate change into long-term planning documents 3

Flooding

Stormwater management (natural or man-made infrastructure) 15



Implementing nature-based solutions for water 3

Hotter summers Heat mapping and thermal imaging 3

More frequent droughts Improve water supply distribution method 3


Declining water quality




Increased frequency of large storms


Projects and policies targeted at those most vulnerable 3

Resilience and resistance measures for buildings 3


More frequent heat waves




Table 13: drivers of deforestation and forest degradation reported by continent14

Drivers of deforestation and forest degradation

Count of drivers across different regions

Africa Europe Latin America North America Total

Small-scale agriculture and colonization 1 16 2 19

Fires 1 1 11 4 17

Livestock 1 1 11 3 16

Unsustainable logging 2 10 2 14

Mining 1 2 8 1 12

Large-scale agriculture 1 8 2 11 14 Analysis of the drivers of deforestation/forest degradation includes information provided by publicly disclosing governments in the comments field in addition to the drivers reported

Infrastructure 1 7 3 11

Charcoal and fuelwood 2 3 5

Hydroelectric power 2 2

Pulp plantations 1 1

Totals 9 5 77 17 108

Table 14: renewable electricity/energy targets by year and region

Government Target type 2020 2025 2030 2040 2045 2050

Abruzzo Renewable energy production 19%

Aland Renewable electricity consumption 60%

Aland Renewable energy consumption 60%

Andalusia Renewable energy consumption 25%

Australian Capital Territory Renewable electricity consumption 100%

Azores Renewable energy production 35%15

Azores Renewable electricity production 61%16

Baden-Württemberg Renewable energy consumption 25% 80%

Baja California Renewable electricity production 10%

Basque Country Renewable energy consumption 21% 40%

Bavaria Renewable electricity production 70%

California Renewable electricity consumption 33% 60%

Cantabria Renewable energy production 42%

Catalonia Renewable energy consumption 50% 100%

Chhattisgarh Renewable energy production 100%17

15 Azores' target is a 2019 target 16 Azores' target is a 2023 target 17 Chhattisgarh’s target is a 2022 target. It covers government-operations only and is not a region-wide target.

Connecticut Renewable electricity consumption 48%

Drenthe Renewable energy production 40%

Estado De México Renewable electricity consumption 35%

Flevoland Renewable energy consumption 44%

Gujarat Renewable electricity production 40%

Hawaii Renewable electricity production 100%

Hesse Renewable energy consumption 100%

Hesse Renewable electricity consumption 25%18 100%

Jämtland Renewable energy consumption 100%

La Reunion Renewable electricity production 50%

Lombardy Renewable energy consumption 16%

Lower Austria Renewable electricity consumption 100%

Lower Saxony Renewable energy consumption 100%

Madeira Renewable electricity production 50%

Minnesota Renewable electricity production 28%

Navarra Renewable electricity consumption 50%

New Caledonia Renewable electricity consumption 100%

New York State Renewable electricity production 70%

North Brabant Renewable energy production 50%

North Denmark Region Renewable energy production 100%

Northwest Territories Renewable energy consumption 40%

Occitanie Renewable energy production 100%

18 Hesse’s target is a 2019 target

Oregon Renewable electricity consumption 50%

Québec Renewable energy production 25%

Queensland Renewable energy production 50%

São Paulo State Renewable energy production 69%

Scotland Renewable electricity consumption 100%

Scotland Renewable energy production 50%

South Holland Renewable energy production 9%

Victoria Renewable energy production 25% 40% 50%

Thuringia Renewable energy consumption 100%

Tocantins Renewable electricity production 20%

Upper Austria Renewable electricity consumption

80%-97%

Wales Renewable electricity consumption 70%

Washington Renewable electricity consumption 15%

Yucatán Renewable energy production 25%19

Table 15: renewable electricity/energy targets by year and region (absolute values)

Government Target type 2020 2030

Brittany Renewable energy production 17143 GWh

North Kalimantan Renewable electricity production 9000 MW

South Holland Renewable electricity production 2.17 GWh

Wales Renewable energy production 1 GW

Wallonia Renewable electricity consumption 5555 GWh 10081 GWh

19 Yucatán's target is a 2024 target

Table 16: region-wide electricity generation breakdown by energy source (%)

State and region Coal Gas Oil Nuclear Biomass Geothermal Hydro Solar Wind

Abruzzo 0 38.9 0 0 0 0 32.7 16.9 7.6

Acre 4 13 5 1 8 0 65 0 4

Akershus 0 0 0 0 0 0 100 0 0

Aland 0 0 4.6 0 0.6 0 0 0 94.8

Amazonas 0 0 0 0 0 0 92.2 0 0

Amazonas (Brazil) 0 49 47 0 0 0 4 0 0

Andalusia 28.6 35.2 0 0 3.8 0 1.5 10.6 19.5

Attica 50 30 10 0 0 0 3 4 3

Australian Capital Territory 42 6 0 0 0 0 4 3 45

Azores 0 0 65 0 0 23 3 0 9

Baja California 0 45.87 0.6 0 0 47.94 0 0 0

Basque Country 0 81.7 0.7 0 5.6 0 5.5 0.5 6

British Columbia 0 3 0 0 5 0 90 0 2

Brittany 0 0 0 0 10 0 15 6 47

California 0.13 40.65 0.02 8.24 2.76 5.32 19.68 16.37 5.9

Campeche 0 20 80 0 0 0 0 0 0

Cantabria 5.43 62.3 0 0 1.6 0 27.57 0.08 3.02

Catalonia 0 29.1 0 53.6 0 0 8.3 1.1 6.1

Chhattisgarh 95.76 0 0 0 0 0 4.05 0.19 0

Colima 15 85 0 0 0 0 0 0 0

Comunidade Intermunicipal do Médio Tejo 45 4 0 0 5 0 24 1 17

Gotland 0 0 0 0 0 0 0 0 93

Greater Wellington Regional Council 0 0 0 0 0 0 0.5 0.1 97

Hawaii 13.2 0 68 0 3.1 3.2 1 2.1 5.5

Huánuco 0 0 0.2 0 0 0 99.8 0 0

Jalisco 28.1 0 0 0 6.6 0 48.4 4.5 12.4

Jämtland 0 0 0 0 1 0 88 0 11

Loreto 0 0 0 0 0 0 0 0 0

Lower Austria 5 11 4 0 7 0 51 2 20

Lower Saxony 16.3 16.4 0.3 25.1 11.8 0 0.3 3.75 24

Madeira 0 16 53 0 4 0 11 4 12

Madre de Dios 0 0 0 0 0 0 0 0 0

Minnesota 38.97 14.71 0.04 23.43 1.61 0 1.89 0.02 17.95

Navarra 0 39.25 0 0 4.78 0 5.67 5.29 45.01

New Caledonia 41 0 47.3 0 0.02 0 9.1 1.3 1.3

New York State 1.1 43.8 0.1 30.3 0 0 19.1 0 2.9

Nord-Trøndelag 0 0 0 0 0 0 98 0 2

Nordland 0 0 0 0 0 0 99 0 1

North Denmark Region 23 11 0 0 2 0 0 2 60

North Rhine-Westphalia 69.6 13.5 1 0 3.7 0 0.4 3.1 8.1

Northwest Territories 0 3.4 19.2 0 0 0 71.4 2.3 3.7

Nuevo León 0 90.02 0 0 0.05 0 0 0.03 9.9

Occitanie 0 0 0 54 2 0 31 5 7

Oppland 0 0 0 0 4.2 0 95.8 0 0

Oregon 2.8 24 0 0.6 0.3 61.1 0.3 9.9

Pernambuco 39.03 0 0 0 7.25 0 35.15 18.32 0.25

Piura Region 0 0 0 0 0 0 100 0 0

Québec 0 0.06 0.28 0 1.01 0 94.12 0 4.53

Queensland 74 18 2 0 2 0 1 3 0

Queretaro 0 88 12 0 0 0 0 0 0

Rhineland-Palatinate 0.5 54.5 0 0 5.8 0 4.7 8.9 25.6

Rio de Janeiro State 8 30 11 46 0.3 0 4 0.3 0.4

Rio Grande do Sul 24.06 0 0 0 0 0 57.37 0 18.57

San Martín 0 0 0 0 0 0 18 0 0

Santa Catarina 76 0 6 0 18 0 0 0 0

São Paulo State 0 6 1 0 9 0 78 0 0

Sardinia 36 0 35 0 6 0 4 6 13

Schleswig-Holstein 8 3.4 1.7 17.7 9.5 0 0 3.8 55.9

Scotland 0.2 8.9 1.4 36.6 4 0 10.9 0.6 34.8

Sonora 38 19 40 0 0 0 2 0 0

South Australia 0 51.3 0 0 0 0 0 8.2 39

South Holland 32 45 4 3 13 0 0 0 0

Victoria 71.2 5.5 0 0 1.5 0 5.7 5.1 11

Thuringia 0 29.75 0 0 9.05 0 1.96 10.99 26.99

Tocantins 0 0 0 0 2 0 98 0 0

Tucuman 0 84 0 0 0.02 0 15.98 0 0

Ucayali 0 0 0 0 0 0 1.3 0 0

Wales 8 69 1.4 0 2 0 1.1 2.9 14.2

Wallonia 0 16.4 0.1 70 2.1 0 0.9 2.9 5.1

Washington 13.39 10.83 0.11 4.19 0.6 0 67.68 0.01 2.84

Western Cape 85.7 3.2 0 5.2 0 0 0 0.9 0.9

Yucatán 0 0 100 0 0 0 0 0 0

Table 17: region-wide energy efficiency targets (as a decrease in energy use)

Government Percent decrease

in energy use Base year Target year

Abruzzo 2.6% 2005 2020

Baden-Württemberg 50% 2010 2050

Brittany 28-32% 2012 2040

Cantabria 16.80% Trend scenario 2020

Catalonia 20% Trend scenario 2020

27% 20 2030

Hawaii 100% 2009 2019

Lombardy 10% 2005 2020

Navarra21

20% Trend scenario 2020



New Caledonia22 20% 2014 2030

25% 2014 2030

North Denmark Region 35% 2012 2020

Occitanie 40% 2015 2050

Piedmont 27% 2030

Scotland 12% 200523 2020

30% 2015 2030

Wallonia 18% 2007 2020

23% 2005 2030

Table 18: region-wide energy efficiency targets (as an increase in energy efficiency)

Government Percent increase

in energy efficiency

Base year Target year

Basque Country 33% 2016 2030

Piedmont 30% 2030

Québec 0 2013 2030 24 2018 2030

Upper Austria 1.5 to 2% per

year 2014 2050

Victoria 25 2015 2020

20 Law 16/2017, of 1 August, on Climate Change (Art. 19.1.a): Reduce final energy consumption almost 2% per year to achieve a minimum of 27% in 2030, excluding non-energetic uses. 21 Navarra’s targets are the same as those established at European Union scale: achieve a 20% efficiency target in 2020, and additional 10% in 2025 and 2030. 22 New Caledonia's 20% target covers primary energy consumption while the 25% target covers final energy consumption. 23 Scotland’s 12% reduction target in total final energy consumption by 2020 is based on a 2005-2007 baseline. 24 Improve the average energy efficiency of Québec society by 1% per year, for the period between 2018 and 2023. 25 The metric used is tonnes of GHG avoided. The Victorian Energy Upgrades program uses greenhouse gas emissions avoided as the metric, one certificate represents one tonne of emissions avoided by activities undertaken under the program.

Table 19: calculated emissions trends since base year


Inventory Year

Calculated emissions reduction since base year

Abruzzo 2006 2012 -18%

Acre 2010 2014 -14%

Aland 2005 2015 -31%

Andalusia 2005 2017 -22%

Attica 2008 2016 -31%

Australian Capital Territory 1990 2017-2018 5%

Azores 1990 2015 21%

Baden-Württemberg 1990 2017 -12%

Baja California 2005 2011-2012 0%

Basque Country 2005 2017 -24%

Bavaria 1990 2015 -91%

British Columbia 2007 2016 -4%

Brittany 2010 2016 -6%

California 1990 2017 -2%

Cantabria 2005 2017 -14%

Catalonia 1990 2017 8%

Chungcheongnam-Do 2005 2016 86%

Colima 2005 2015 -59%

Comunidade Intermunicipal do Médio Tejo 2008 2014 -20%

Connecticut 1990 2016 -9%

Drenthe 1990 2017 -4%

Estado De México 2010 2016 -22%

Gotland 1990 2017 -6%

Greater Wellington Regional Council 2001 2014-2015 -44%

Guanajuato 2005 2013 -21%

Hawaii 1990 2015 -7%

Helsinki-Uusimaa 1990 2016 -18%

Hesse 1990 2016 -21%

Jämtland 1990 2015 -37%

La Réunion 2011 2015 -13%

Lombardy 2005 2017 -23%

Lower Austria 2005 2017 -48%

Lower Saxony 1990 2015 -14%

Minnesota 2005 2016 -20%

Navarra 2005 2017 -16%

New Caledonia 2014 2018 49%

New York State 1990 2016 -13%

Newfoundland and Labrador 1990 2017 12%

Nordland 2009 2017 12%

North Brabant 2010 2017 -6%

North Denmark Region 2010 2016 -15%

North Rhine-Westphalia 1990 2017 -25%

Northwest Territories 2005 2017 -19%

Oaxaca 2013 2013 -74%

Oregon 1990 2017 15%

Québec 1990 2016 -9%

Queensland 2005 2016-2017 -21%

Rhineland-Palatinate 1990 2015 -37%

Rio de Janeiro State 2005 2015 40%

Schleswig-Holstein 1990 2017 -25%

Scotland 1990 2017 -47%

Sonora 1990 2014-2015 54%

South Australia 1990 2016-2017 -39%

South Holland 1990 2017 14%

Victoria 2005 2015 -11%

Thuringia 1990 2016 -61%

Wales 1990 2017 -25%

Wallonia 1990 2017 -38%

Washington 1990 2015 -36%

Western Cape 2009 2015-2016 3%

References

Climate Analytics and NewClimate Institute (2019) Climate Action Tracker. Available at:

https://climateactiontracker.org/countries/

Grubler, A., Wilson, C., Bento, N. et al. (2018) A low energy demand scenario for meeting the 1.5 °C

target and sustainable development goals without negative emission technologies. Nat Energy 3, 515–

527. doi:10.1038/s41560-018-0172-6. Available at: https://www.nature.com/articles/s41560-018-

0172-6#citeas

Huppmann, D. et al. (2018) IAMC 1.5°C Scenario Explorer and Data hosted by IIASA release 2.0.

Integrated Assessment Modeling Consortium & International Institute for Applied Systems Analysis.

Available at: https://data.ene.iiasa.ac.at/iamc-1.5c-explorer/#/login?redirect=%2Fworkspaces

World Bank Group (2019) Population Estimates and Projections. Data Catalog. Available at:


https://climateactiontracker.org/countries/

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https://www.nature.com/articles/s41560-018-0172-6#citeas



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